Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Unified Algorithms for RL with Decision-Estimation Coefficients: PAC, Reward-Free, Preference-Based Learning, and Beyond
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2209.11745.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T09:17:56.858336Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T09:23:16.496406Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 43508701-9f48-4bdc-8ae4-da6082868c7a · inbound
Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation cites this paper.
Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation Unified Algorithms for RL with Decision-Estimation Coefficients: PAC, Reward-Free, Preference-Based Learning, and Beyond
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T06:00:35.958127Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 6588cd9b-2562-4761-ad51-59e602d11e84 · inbound
The Sample Complexity of Multiclass and Sparse Contextual Bandits cites this paper.
The Sample Complexity of Multiclass and Sparse Contextual Bandits Unified Algorithms for RL with Decision-Estimation Coefficients: PAC, Reward-Free, Preference-Based Learning, and Beyond
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T09:23:16.498057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.